Journal Article

DZNE-2024-01278

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Machine learning reveals prominent spontaneous behavioral changes and treatment efficacy in humanized and transgenic Alzheimer's disease models.

Miller, S. R. ; Luxem, K.DZNE* ; Lauderdale, K. ; Nambiar, P. ; Honma, P. S. ; Ly, K. K. ; Bangera, S. ; Bullock, M. ; Shin, J. ; Kaliss, N. ; Qiu, Y. ; Cai, C. ; Shen, K. ; Mallen, K. D. ; Yan, Z. ; Mendiola, A. S. ; Saito, T. ; Saido, T. C. ; Pico, A. R. ; Thomas, R. ; Roberson, E. D. ; Akassoglou, K. ; Bauer, P.DZNE* ; Remy, S.DZNE* ; Palop, J. J.

2024
Elsevier [New York, NY]

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Please use a persistent id in citations: doi:10.1016/j.celrep.2024.114870

Abstract: Computer-vision and machine-learning (ML) approaches are being developed to provide scalable, unbiased, and sensitive methods to assess mouse behavior. Here, we used the ML-based variational animal motion embedding (VAME) segmentation platform to assess spontaneous behavior in humanized App knockin and transgenic APP models of Alzheimer's disease (AD) and to test the role of AD-related neuroinflammation in these behavioral manifestations. We found marked alterations in spontaneous behavior in AppNL-G-F and 5xFAD mice, including age-dependent changes in motif utilization, disorganized behavioral sequences, increased transitions, and randomness. Notably, blocking fibrinogen-microglia interactions in 5xFAD-Fggγ390-396A mice largely prevented spontaneous behavioral alterations, indicating a key role for neuroinflammation. Thus, AD-related spontaneous behavioral alterations are prominent in knockin and transgenic models and sensitive to therapeutic interventions. VAME outcomes had higher specificity and sensitivity than conventional behavioral outcomes. We conclude that spontaneous behavior effectively captures age- and sex-dependent disease manifestations and treatment efficacy in AD models.

Keyword(s): Alzheimer Disease: pathology (MeSH) ; Alzheimer Disease: genetics (MeSH) ; Animals (MeSH) ; Machine Learning (MeSH) ; Humans (MeSH) ; Mice, Transgenic (MeSH) ; Disease Models, Animal (MeSH) ; Mice (MeSH) ; Behavior, Animal (MeSH) ; Male (MeSH) ; Female (MeSH) ; Treatment Outcome (MeSH) ; Amyloid beta-Protein Precursor: genetics (MeSH) ; Amyloid beta-Protein Precursor: metabolism (MeSH) ; Mice, Inbred C57BL (MeSH) ; App-KI ; CP: Neuroscience ; DeepLabCut ; Keypoint-MoSeq ; amyloid ; behavioral segmentation ; cognition ; naturalistic behavior ; open field ; pose estimation ; preclinical

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Contributing Institute(s):

1. Neuronal Networks (AG Remy)

Research Program(s):

1. 351 - Brain Function (POF4-351) (POF4-351)

Appears in the scientific report 2024

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Database coverage:
; ; ; ; Article Processing Charges ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; DOAJ Seal ; Essential Science Indicators ; Fees ; IF >= 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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